Paper Info
Title
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale.
Abstract
We present Open Images V4, a dataset of 9.2M images with unified annotations for image classification, object detection and visual relationship detection. The images have a Creative Commons Attribution license that allows to share and adapt the material, and they have been collected from Flickr without a predefined list of class names or tags, leading to natural class statistics and avoiding an initial design bias. Open Images V4 offers large scale across several dimensions: 30.1M image-level labels for 19.8k concepts, 15.4M bounding boxes for 600 object classes, and 375k visual relationship annotations involving 57 classes. For object detection in particular, we provide 15x more bounding boxes than the next largest datasets (15.4M boxes on 1.9M images). The images often show complex scenes with several objects (8 annotated objects per image on average). We annotated visual relationships between them, which support visual relationship detection, an emerging task that requires structured reasoning. We provide in-depth comprehensive statistics about the dataset, we validate the quality of the annotations, and we study how the performance of many modern models evolves with increasing amounts of training data. We hope that the scale, quality, and variety of Open Images V4 will foster further research and innovation even beyond the areas of image classification, object detection, and visual relationship detection.
Year
Venue
DocType
2018
arXiv: Computer Vision and Pattern Recognition
Journal
Volume
Citations 
PageRank 
abs/1811.00982
30
0.76
References 
Authors
3
11
Name
Order
Citations
PageRank
Alina Kuznetsova12069.07
Hassan Rom2301.10
Neil G. Alldrin32708.45
J. R. R. Uijlings4125295.20
Ivan Krasin5301.10
Jordi Pont-Tuset665632.22
Shahab Kamali7300.76
Stefan Popov81255.70
Matteo Malloci9300.76
Tom Duerig101566.20
Vittorio Ferrari115369284.83